Git Product home page Git Product logo

testing.postgresql's Introduction

About

testing.postgresql automatically setups a postgresql instance in a temporary directory, and destroys it after testing.

https://travis-ci.org/tk0miya/testing.postgresql.svg?branch=master https://coveralls.io/repos/tk0miya/testing.postgresql/badge.png?branch=master
Documentation
https://github.com/tk0miya/testing.postgresql
Issues
https://github.com/tk0miya/testing.postgresql/issues
Download
https://pypi.python.org/pypi/testing.postgresql

Install

Use pip:

$ pip install testing.postgresql

And testing.postgresql requires PostgreSQL server in your PATH.

Usage

Create PostgreSQL instance using testing.postgresql.Postgresql:

import testing.postgresql
from sqlalchemy import create_engine

# Lanuch new PostgreSQL server
with testing.postgresql.Postgresql() as postgresql:
    # connect to PostgreSQL
    engine = create_engine(postgresql.url())

    # if you use postgresql or other drivers:
    #   import psycopg2
    #   db = psycopg2.connect(**postgresql.dsn())

    #
    # do any tests using PostgreSQL...
    #

# PostgreSQL server is terminated here

testing.postgresql.Postgresql executes initdb and postgres on instantiation. On deleting Postgresql object, it terminates PostgreSQL instance and removes temporary directory.

If you want a database including tables and any fixtures for your apps, use copy_data_from keyword:

# uses a copy of specified data directory of PostgreSQL.
postgresql = testing.postgresql.Postgresql(copy_data_from='/path/to/your/database')

For example, you can setup new PostgreSQL server for each testcases on setUp() method:

import unittest
import testing.postgresql

class MyTestCase(unittest.TestCase):
    def setUp(self):
        self.postgresql = testing.postgresql.Postgresql()

    def tearDown(self):
        self.postgresql.stop()

To make your tests faster

testing.postgresql.Postgresql invokes initdb command on every instantiation. That is very simple. But, in many cases, it is very waste that generating brandnew database for each testcase.

To optimize the behavior, use testing.postgresql.PostgresqlFactory. The factory class is able to cache the generated database beyond the testcases, and it reduces the number of invocation of initdb command:

import unittest
import testing.postgresql

# Generate Postgresql class which shares the generated database
Postgresql = testing.postgresql.PostgresqlFactory(cache_initialized_db=True)


def tearDownModule(self):
    # clear cached database at end of tests
    Postgresql.clear_cache()


class MyTestCase(unittest.TestCase):
    def setUp(self):
        # Use the generated Postgresql class instead of testing.postgresql.Postgresql
        self.postgresql = Postgresql()

    def tearDown(self):
        self.postgresql.stop()

If you want to insert fixtures to the cached database, use initdb_handler option:

# create initial data on create as fixtures into the database
def handler(postgresql):
    conn = psycopg2.connect(**postgresql.dsn())
    cursor = conn.cursor()
    cursor.execute("CREATE TABLE hello(id int, value varchar(256))")
    cursor.execute("INSERT INTO hello values(1, 'hello'), (2, 'ciao')")
    cursor.close()
    conn.commit()
    conn.close()

# Use `handler()` on initialize database
Postgresql = testing.postgresql.PostgresqlFactory(cache_initialized_db=True,
                                                  on_initialized=handler)

Requirements

  • Python 2.7, 3.4, 3.5, 3.6
  • pg8000 1.10

License

Apache License 2.0

History

1.3.0 (2016-02-03)

  • Add testing.postgresql.PostgresqlFactory
  • Depend on testing.common.database package

1.2.1 (2015-08-22)

  • Fix bug:
    • Close #3 Fix AttributeError on end of tests

1.2.0 (2015-05-17)

  • Use pg8000 for connector to create test database
  • Connect to postgres to create test database (instead of template1)

1.1.2 (2015-04-06)

  • Fix bugs:
    • Do not call os.getpid() on destructor (if not needed)
    • Raise detailed RuntimeError if initdb exits non-zero

1.1.1 (2015-01-18)

  • Disable logging_collector feature (For Fedora)
  • Fix bugs:
    • MacPorts default path is /opt/local/lib/postgresql*, no dash

1.1.0 (2014-12-20)

  • Invoke 'postgres' command instead of 'postmaster'

1.0.6 (2014-07-19)

  • Fix #1 Dirty postmaster shut down

1.0.5 (2014-07-19)

  • Fix path for PostgreSQL
  • Use absolute path for which command

1.0.4 (2014-06-19)

  • Fix timeout on terminating postgresql
  • Support PostgreSQL on /usr/local/bin (cf. FreeBSD ports)
  • Fix bugs

1.0.3 (2014-06-11)

  • Fix ImportError if caught SIGINT on py3

1.0.2 (2013-12-06)

  • Change behavior: Postgresql#stop() cleans workdir
  • Fix caught AttributeError on object deletion

1.0.1 (2013-12-05)

  • Add @skipIfNotInstalled decorator (alias of skipIfNotFound)
  • Suport python 2.6 and 3.2

1.0.0 (2013-12-04)

  • Add @skipIfNotFound decorator

0.1.0 (2013-11-26)

  • First release

testing.postgresql's People

Contributors

tk0miya avatar eradman avatar sirex avatar adelosa avatar tokenmathguy avatar sorki avatar rutsky avatar gliptak avatar ju2wheels avatar lpsinger avatar graingert avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.